Process optimization activities for downstream and midstream operations are often cumbersome and onerous due to scale and complexity, while existing workflows are heavily reliant upon legacy technologies, and disparate and disconnected tools. The Process Optimization solution can help overcome these challenges and drive operational enhancements by improving unit throughput, product quality and product yields, in addition to improving energy consumption.
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The AWS Process Optimization solution is a cloud-native solution that uses innovative services like Amazon SageMaker to build, train, and deploy ML models, and AWS IoT TwinMaker to easily create digital twins of real-world assets. The AI-powered offering is built on a foundational data architecture for open-loop insights, predictions, and recommendations. Leveraging ML, the solution provides models and supporting infrastructure to infer suggested process changes. Artificial intelligence is used for higher level goal-oriented inference providing computer vision, conversational interfaces, and chatbots for improved information accessibility and insight detection. The Process Optimization solution’s digital twin simulation capabilities help users to gain a virtual representation of assets for process and visualization oversight. This allows operators to simulate proposed facility changes, streamline remote job planning, and re-optimize following unplanned upsets and events.
Process optimization helps improve operations to maximize efficiency, productivity, reliability, and profitability. Because of the scale and complexity of energy and utility plants, process optimization activities are often cumbersome and onerous. The Process Optimization solutions on AWS are cloud-native offerings, powered by artificial intelligence (AI), and built to provide data-driven insights, predictions, and recommendations that improve process safety, reliability, and performance. These solutions support engineers and operators in real-time optimization efforts, including improving throughput, product quality, yields, energy efficiencies, and emissions management.
